Robotic Process Automation in Banking
Did you know that human mistake in the banking industry results in over $878,000 in wasted time and labor each year? It is evident that the desire for change on the part of banking and financial services is not surprising.
Implementing robotic process automation makes sense since the human error can have a high financial cost in the BFSI industry. A Mckinsey report claims that RPA can automate more than 30% of tasks in about 60% of occupations.
The banking sector is anticipated to grow as business procedures across organizations change. The urge to automate superfluous procedures and provide end users control is expected to drive the sector over the next few years.
Automation adopters will concentrate on four areas: Quick Automation, Auto Decision, Data Security, and Instant Scalability.
BFSI is a tremendously competitive industry; banks and other financial institutions must continuously innovate, stay competitive, and deliver excellent user experiences. This is especially true given the significant counter-competition from FinTech and other virtual banking alternatives.
Banks and other financial institutions are under a lot of pressure to reduce costs and boost output. The lack of qualified workers, the need to increase process effectiveness, and the sharp rise in labor costs all contribute to the adoption of RPA in banking business.
Top 10 Benefits of RPA in Banking and Finance
You must consider which tasks in your banking and financial organization to automate.
Enhanced Productivity and Efficiency
Another advantage of RPA systems is how easily and quickly they complete tasks since they listen to and carry out instructions without any space for ambiguity. Robotic accounting procedures don’t have any drawbacks, in contrast to manual ones. Gartner estimates that banking automation can prevent up to 25,000 hours of unnecessary work caused by human mistakes.
By addressing the need for bots to respond to events at record speed, robots’ high scalability enables you to manage big volumes during peak business hours. In addition, by relieving bank personnel of tedious activities, RPA deployment enables the bank to concentrate more on creative business growth ideas.
Accurate Information Extraction
Because there is a vast amount of consumer data saved in systems, RPA, a combination of AI and machine learning, can readily store the necessary data for any desired query. Additionally, automated processing leverages third-party databases to gather information when there are errors or blank fields on bills in order to streamline Accounts Receivable and Accounts Payable procedures. However, similar operations can be completed quickly with RPA and particularly Intelligent Automation.
Cut Down Expenses
The requirement for manual intervention will diminish as a result of the elimination of redundancy, which will allow banking and financial companies to drastically cut their additional expenses for resources, systems, and staff.
Repeated tasks like manually processing data and adding fresh data could be avoided by employees. The financial sector can employ this technology to boost efficiency, consume less energy, and cut back on time, which can lower expenses by around 25–50%.
Increased Accuracy and Dependability
It is natural for people to make mistakes. However, occasionally even the smallest errors could result in serious mistakes that would cost the company a significant amount of money. Unfortunate circumstances may even result in the customers’ excellent reputation being lost.
But the introduction of RPA systems can quickly allay these concerns. The systems will conduct the procedure precisely and effectively with RPA. With the most recent technical marvels like AI and ML, massive amounts of data and processes may be managed effectively. Additionally, RPA solutions are accessible 24/7 and are not hindered by data failures. The data is effectively, automatically, and frequently backed up. Therefore, even if an unexpected event or downtime occurs, it will only stay a short while, and the process will resume as usual very quickly.
According to Grand View Research, the banking and financial services sector, which accounted for over 29% of global revenue, was at the forefront of RPA adoption in 2019.
Better Compliance and Risk Management
In order to comply with regulatory requirements and ensure meticulous record-keeping for potential audits, banking organizations must align their operational practices with applicable regulations. The banking industry, in particular, faces rigorous regulatory standards that necessitate strict adherence.
Managing a lot of data coming from multiple resources and monitoring them on time takes a lot of effort from banking employees. Here RPA bot can be programmed to automatically perform real-time monitoring, and analyze the data to make sure business processes adhere to regulations.
Having a lot of transactions happening across the banking operations, banking employees must keep all the data in check to prevent any fraudulent activities. Instead of banking employees handling the transaction and analyzing it in real-time, RPA can take over this repetitive process and analyze the transaction in real-time. Also, these RPA bots can also generate alerts whenever any fraudulent activities occur. That’s how RPA enables faster defect detection and maintains transparency.
Faster Loan Processing
According to a poll conducted by Moody’s Analytics, manual data entry is the biggest challenge in loan origination. As banks receive these loan applications in high amounts, banking employees need to extract, analyze, and verify the data before processing loans. Here RPA can reduce the time involved in loan application processing using intelligent document processing to extract, analyze, and process the data, and the RPA bot can facilitate seamless communication with customers for information about approval and other information
With a lot of processes encircling the banking operations, banking employees receive queries 24/7. Checking these queries extracting the information and routing the ticket to the right banking agents for instant resolution can be done by using an RPA bot. Also, this RPA bot can be available 24/7 and with pre-defined rules, it can offer self-service to customers as well.
Improved Data Analytics
RPA can automate data extraction and transformation tasks, making it easier for banks to collect and analyze customer data. This facilitates data insights in one glance and enables banking organizations for data-driven decision-making, allowing banks to offer targeted products and services.
As opportunistic, system-based solutions that are quicker and simpler to adopt than extensive transformations, several banks, and financial institutions have started the journey of implementing RPA in their operations.
Robotic process automation, or RPA, services, which automate manual, repetitive, and time-consuming operations, can aid in the banking industry’s digital transformation if properly applied. Increased output, a considerable drop in error rates, and rapid turnaround times would result from automating such repetitive activities.
Throughout the RPA deployment process, having a partner with a track record of proficiency in RPA tools, technologies, and staffing is essential.
This will benefit banks and other financial organizations, but it will also show them when and how to transition from RPA to AI and other advanced technologies. And, who better than the RPA innovators – AutomationEdge!